[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6F6K7VEH197RFYCDRPCX3RP":3,"skill-same:01M6F6K7VEH197RFYCDRPCX3RP":79},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":47,"linkOnly":48,"markdownContent":49,"markdownBody":50,"frontMatter":51,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":6,"ownerHtmlUrl":61,"ownerBlogUrl":62,"ownerDescription":63,"updatedAt":64,"install":65,"resources":78},"01M6F6K7VEH197RFYCDRPCX3RP","exa-load-scale",null,"Implement Exa load testing, auto-scaling, and capacity planning strategies.\nUse when running performance tests, configuring horizontal scaling,\nor planning capacity for Exa integrations.\nTrigger with phrases like \"exa load test\", \"exa scale\",\n\"exa performance test\", \"exa capacity\", \"exa k6\", \"exa benchmark\".","Dicklesworthstone\u002Fpi_agent_rust","Dicklesworthstone","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F35050222?v=4","01M6CG26AR942CSVMN1M5E3DSE","Jeff Emanuel","01M6CG26EPP71PSHW1VDS71121",1981,"MIT","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Fexa-pack\u002Fskills\u002Fexa-load-scale\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46],"load","exa load scale","scale","exa","auto","when","performance test","Auto-Scaling","io","scaling","strategies","capacity planning","testing","edit","write","read","integrations","Bash","k6","kubectl","benchmark","load testing","performance","2026-11-10 10:12:30",false,"---\nname: exa-load-scale\ndescription: |\n  Implement Exa load testing, auto-scaling, and capacity planning strategies.\n  Use when running performance tests, configuring horizontal scaling,\n  or planning capacity for Exa integrations.\n  Trigger with phrases like \"exa load test\", \"exa scale\",\n  \"exa performance test\", \"exa capacity\", \"exa k6\", \"exa benchmark\".\nallowed-tools: Read, Write, Edit, Bash(k6:*), Bash(kubectl:*)\nversion: 1.0.0\nlicense: MIT\nauthor: Jeremy Longshore \u003Cjeremy@intentsolutions.io>\n---\n\n# Exa Load & Scale\n\n## Overview\nLoad testing, scaling strategies, and capacity planning for Exa integrations.\n\n## Prerequisites\n- k6 load testing tool installed\n- Kubernetes cluster with HPA configured\n- Prometheus for metrics collection\n- Test environment API keys\n\n## Load Testing with k6\n\n### Basic Load Test\n```javascript\n\u002F\u002F exa-load-test.js\nimport http from 'k6\u002Fhttp';\nimport { check, sleep } from 'k6';\n\nexport const options = {\n  stages: [\n    { duration: '2m', target: 10 },   \u002F\u002F Ramp up\n    { duration: '5m', target: 10 },   \u002F\u002F Steady state\n    { duration: '2m', target: 50 },   \u002F\u002F Ramp to peak\n    { duration: '5m', target: 50 },   \u002F\u002F Stress test\n    { duration: '2m', target: 0 },    \u002F\u002F Ramp down\n  ],\n  thresholds: {\n    http_req_duration: ['p(95)\u003C500'],\n    http_req_failed: ['rate\u003C0.01'],\n  },\n};\n\nexport default function () {\n  const response = http.post(\n    'https:\u002F\u002Fapi.exa.com\u002Fv1\u002Fresource',\n    JSON.stringify({ test: true }),\n    {\n      headers: {\n        'Content-Type': 'application\u002Fjson',\n        'Authorization': `Bearer ${__ENV.EXA_API_KEY}`,\n      },\n    }\n  );\n\n  check(response, {\n    'status is 200': (r) => r.status === 200,\n    'latency \u003C 500ms': (r) => r.timings.duration \u003C 500,\n  });\n\n  sleep(1);\n}\n```\n\n### Run Load Test\n```bash\n# Install k6\nbrew install k6  # macOS\n# or: sudo apt install k6  # Linux\n\n# Run test\nk6 run --env EXA_API_KEY=${EXA_API_KEY} exa-load-test.js\n\n# Run with output to InfluxDB\nk6 run --out influxdb=http:\u002F\u002Flocalhost:8086\u002Fk6 exa-load-test.js\n```\n\n## Scaling Patterns\n\n### Horizontal Scaling\n```yaml\n# kubernetes HPA\napiVersion: autoscaling\u002Fv2\nkind: HorizontalPodAutoscaler\nmetadata:\n  name: exa-integration-hpa\nspec:\n  scaleTargetRef:\n    apiVersion: apps\u002Fv1\n    kind: Deployment\n    name: exa-integration\n  minReplicas: 2\n  maxReplicas: 20\n  metrics:\n    - type: Resource\n      resource:\n        name: cpu\n        target:\n          type: Utilization\n          averageUtilization: 70\n    - type: Pods\n      pods:\n        metric:\n          name: exa_queue_depth\n        target:\n          type: AverageValue\n          averageValue: 100\n```\n\n### Connection Pooling\n```typescript\nimport { Pool } from 'generic-pool';\n\nconst exaPool = Pool.create({\n  create: async () => {\n    return new ExaClient({\n      apiKey: process.env.EXA_API_KEY!,\n    });\n  },\n  destroy: async (client) => {\n    await client.close();\n  },\n  max: 20,\n  min: 5,\n  idleTimeoutMillis: 30000,\n});\n\nasync function withExaClient\u003CT>(\n  fn: (client: ExaClient) => Promise\u003CT>\n): Promise\u003CT> {\n  const client = await exaPool.acquire();\n  try {\n    return await fn(client);\n  } finally {\n    exaPool.release(client);\n  }\n}\n```\n\n## Capacity Planning\n\n### Metrics to Monitor\n| Metric | Warning | Critical |\n|--------|---------|----------|\n| CPU Utilization | > 70% | > 85% |\n| Memory Usage | > 75% | > 90% |\n| Request Queue Depth | > 100 | > 500 |\n| Error Rate | > 1% | > 5% |\n| P95 Latency | > 1000ms | > 3000ms |\n\n### Capacity Calculation\n```typescript\ninterface CapacityEstimate {\n  currentRPS: number;\n  maxRPS: number;\n  headroom: number;\n  scaleRecommendation: string;\n}\n\nfunction estimateExaCapacity(\n  metrics: SystemMetrics\n): CapacityEstimate {\n  const currentRPS = metrics.requestsPerSecond;\n  const avgLatency = metrics.p50Latency;\n  const cpuUtilization = metrics.cpuPercent;\n\n  \u002F\u002F Estimate max RPS based on current performance\n  const maxRPS = currentRPS \u002F (cpuUtilization \u002F 100) * 0.7; \u002F\u002F 70% target\n  const headroom = ((maxRPS - currentRPS) \u002F currentRPS) * 100;\n\n  return {\n    currentRPS,\n    maxRPS: Math.floor(maxRPS),\n    headroom: Math.round(headroom),\n    scaleRecommendation: headroom \u003C 30\n      ? 'Scale up soon'\n      : headroom \u003C 50\n      ? 'Monitor closely'\n      : 'Adequate capacity',\n  };\n}\n```\n\n## Benchmark Results Template\n\n```markdown\n## Exa Performance Benchmark\n**Date:** YYYY-MM-DD\n**Environment:** [staging\u002Fproduction]\n**SDK Version:** X.Y.Z\n\n### Test Configuration\n- Duration: 10 minutes\n- Ramp: 10 → 100 → 10 VUs\n- Target endpoint: \u002Fv1\u002Fresource\n\n### Results\n| Metric | Value |\n|--------|-------|\n| Total Requests | 50,000 |\n| Success Rate | 99.9% |\n| P50 Latency | 120ms |\n| P95 Latency | 350ms |\n| P99 Latency | 800ms |\n| Max RPS Achieved | 150 |\n\n### Observations\n- [Key finding 1]\n- [Key finding 2]\n\n### Recommendations\n- [Scaling recommendation]\n```\n\n## Instructions\n\n### Step 1: Create Load Test Script\nWrite k6 test script with appropriate thresholds.\n\n### Step 2: Configure Auto-Scaling\nSet up HPA with CPU and custom metrics.\n\n### Step 3: Run Load Test\nExecute test and collect metrics.\n\n### Step 4: Analyze and Document\nRecord results in benchmark template.\n\n## Output\n- Load test script created\n- HPA configured\n- Benchmark results documented\n- Capacity recommendations defined\n\n## Error Handling\n| Issue | Cause | Solution |\n|-------|-------|----------|\n| k6 timeout | Rate limited | Reduce RPS |\n| HPA not scaling | Wrong metrics | Verify metric name |\n| Connection refused | Pool exhausted | Increase pool size |\n| Inconsistent results | Warm-up needed | Add ramp-up phase |\n\n## Examples\n\n### Quick k6 Test\n```bash\nk6 run --vus 10 --duration 30s exa-load-test.js\n```\n\n### Check Current Capacity\n```typescript\nconst metrics = await getSystemMetrics();\nconst capacity = estimateExaCapacity(metrics);\nconsole.log('Headroom:', capacity.headroom + '%');\nconsole.log('Recommendation:', capacity.scaleRecommendation);\n```\n\n### Scale HPA Manually\n```bash\nkubectl scale deployment exa-integration --replicas=5\nkubectl get hpa exa-integration-hpa\n```\n\n## Resources\n- [k6 Documentation](https:\u002F\u002Fk6.io\u002Fdocs\u002F)\n- [Kubernetes HPA](https:\u002F\u002Fkubernetes.io\u002Fdocs\u002Ftasks\u002Frun-application\u002Fhorizontal-pod-autoscale\u002F)\n- [Exa Rate Limits](https:\u002F\u002Fdocs.exa.com\u002Frate-limits)\n\n## Next Steps\nFor reliability patterns, see `exa-reliability-patterns`.","# Exa Load & Scale\n\n## Overview\nLoad testing, scaling strategies, and capacity planning for Exa integrations.\n\n## Prerequisites\n- k6 load testing tool installed\n- Kubernetes cluster with HPA configured\n- Prometheus for metrics collection\n- Test environment API keys\n\n## Load Testing with k6\n\n### Basic Load Test\n```javascript\n\u002F\u002F exa-load-test.js\nimport http from 'k6\u002Fhttp';\nimport { check, sleep } from 'k6';\n\nexport const options = {\n  stages: [\n    { duration: '2m', target: 10 },   \u002F\u002F Ramp up\n    { duration: '5m', target: 10 },   \u002F\u002F Steady state\n    { duration: '2m', target: 50 },   \u002F\u002F Ramp to peak\n    { duration: '5m', target: 50 },   \u002F\u002F Stress test\n    { duration: '2m', target: 0 },    \u002F\u002F Ramp down\n  ],\n  thresholds: {\n    http_req_duration: ['p(95)\u003C500'],\n    http_req_failed: ['rate\u003C0.01'],\n  },\n};\n\nexport default function () {\n  const response = http.post(\n    'https:\u002F\u002Fapi.exa.com\u002Fv1\u002Fresource',\n    JSON.stringify({ test: true }),\n    {\n      headers: {\n        'Content-Type': 'application\u002Fjson',\n        'Authorization': `Bearer ${__ENV.EXA_API_KEY}`,\n      },\n    }\n  );\n\n  check(response, {\n    'status is 200': (r) => r.status === 200,\n    'latency \u003C 500ms': (r) => r.timings.duration \u003C 500,\n  });\n\n  sleep(1);\n}\n```\n\n### Run Load Test\n```bash\n# Install k6\nbrew install k6  # macOS\n# or: sudo apt install k6  # Linux\n\n# Run test\nk6 run --env EXA_API_KEY=${EXA_API_KEY} exa-load-test.js\n\n# Run with output to InfluxDB\nk6 run --out influxdb=http:\u002F\u002Flocalhost:8086\u002Fk6 exa-load-test.js\n```\n\n## Scaling Patterns\n\n### Horizontal Scaling\n```yaml\n# kubernetes HPA\napiVersion: autoscaling\u002Fv2\nkind: HorizontalPodAutoscaler\nmetadata:\n  name: exa-integration-hpa\nspec:\n  scaleTargetRef:\n    apiVersion: apps\u002Fv1\n    kind: Deployment\n    name: exa-integration\n  minReplicas: 2\n  maxReplicas: 20\n  metrics:\n    - type: Resource\n      resource:\n        name: cpu\n        target:\n          type: Utilization\n          averageUtilization: 70\n    - type: Pods\n      pods:\n        metric:\n          name: exa_queue_depth\n        target:\n          type: AverageValue\n          averageValue: 100\n```\n\n### Connection Pooling\n```typescript\nimport { Pool } from 'generic-pool';\n\nconst exaPool = Pool.create({\n  create: async () => {\n    return new ExaClient({\n      apiKey: process.env.EXA_API_KEY!,\n    });\n  },\n  destroy: async (client) => {\n    await client.close();\n  },\n  max: 20,\n  min: 5,\n  idleTimeoutMillis: 30000,\n});\n\nasync function withExaClient\u003CT>(\n  fn: (client: ExaClient) => Promise\u003CT>\n): Promise\u003CT> {\n  const client = await exaPool.acquire();\n  try {\n    return await fn(client);\n  } finally {\n    exaPool.release(client);\n  }\n}\n```\n\n## Capacity Planning\n\n### Metrics to Monitor\n| Metric | Warning | Critical |\n|--------|---------|----------|\n| CPU Utilization | > 70% | > 85% |\n| Memory Usage | > 75% | > 90% |\n| Request Queue Depth | > 100 | > 500 |\n| Error Rate | > 1% | > 5% |\n| P95 Latency | > 1000ms | > 3000ms |\n\n### Capacity Calculation\n```typescript\ninterface CapacityEstimate {\n  currentRPS: number;\n  maxRPS: number;\n  headroom: number;\n  scaleRecommendation: string;\n}\n\nfunction estimateExaCapacity(\n  metrics: SystemMetrics\n): CapacityEstimate {\n  const currentRPS = metrics.requestsPerSecond;\n  const avgLatency = metrics.p50Latency;\n  const cpuUtilization = metrics.cpuPercent;\n\n  \u002F\u002F Estimate max RPS based on current performance\n  const maxRPS = currentRPS \u002F (cpuUtilization \u002F 100) * 0.7; \u002F\u002F 70% target\n  const headroom = ((maxRPS - currentRPS) \u002F currentRPS) * 100;\n\n  return {\n    currentRPS,\n    maxRPS: Math.floor(maxRPS),\n    headroom: Math.round(headroom),\n    scaleRecommendation: headroom \u003C 30\n      ? 'Scale up soon'\n      : headroom \u003C 50\n      ? 'Monitor closely'\n      : 'Adequate capacity',\n  };\n}\n```\n\n## Benchmark Results Template\n\n```markdown\n## Exa Performance Benchmark\n**Date:** YYYY-MM-DD\n**Environment:** [staging\u002Fproduction]\n**SDK Version:** X.Y.Z\n\n### Test Configuration\n- Duration: 10 minutes\n- Ramp: 10 → 100 → 10 VUs\n- Target endpoint: \u002Fv1\u002Fresource\n\n### Results\n| Metric | Value |\n|--------|-------|\n| Total Requests | 50,000 |\n| Success Rate | 99.9% |\n| P50 Latency | 120ms |\n| P95 Latency | 350ms |\n| P99 Latency | 800ms |\n| Max RPS Achieved | 150 |\n\n### Observations\n- [Key finding 1]\n- [Key finding 2]\n\n### Recommendations\n- [Scaling recommendation]\n```\n\n## Instructions\n\n### Step 1: Create Load Test Script\nWrite k6 test script with appropriate thresholds.\n\n### Step 2: Configure Auto-Scaling\nSet up HPA with CPU and custom metrics.\n\n### Step 3: Run Load Test\nExecute test and collect metrics.\n\n### Step 4: Analyze and Document\nRecord results in benchmark template.\n\n## Output\n- Load test script created\n- HPA configured\n- Benchmark results documented\n- Capacity recommendations defined\n\n## Error Handling\n| Issue | Cause | Solution |\n|-------|-------|----------|\n| k6 timeout | Rate limited | Reduce RPS |\n| HPA not scaling | Wrong metrics | Verify metric name |\n| Connection refused | Pool exhausted | Increase pool size |\n| Inconsistent results | Warm-up needed | Add ramp-up phase |\n\n## Examples\n\n### Quick k6 Test\n```bash\nk6 run --vus 10 --duration 30s exa-load-test.js\n```\n\n### Check Current Capacity\n```typescript\nconst metrics = await getSystemMetrics();\nconst capacity = estimateExaCapacity(metrics);\nconsole.log('Headroom:', capacity.headroom + '%');\nconsole.log('Recommendation:', capacity.scaleRecommendation);\n```\n\n### Scale HPA Manually\n```bash\nkubectl scale deployment exa-integration --replicas=5\nkubectl get hpa exa-integration-hpa\n```\n\n## Resources\n- [k6 Documentation](https:\u002F\u002Fk6.io\u002Fdocs\u002F)\n- [Kubernetes HPA](https:\u002F\u002Fkubernetes.io\u002Fdocs\u002Ftasks\u002Frun-application\u002Fhorizontal-pod-autoscale\u002F)\n- [Exa Rate Limits](https:\u002F\u002Fdocs.exa.com\u002Frate-limits)\n\n## Next Steps\nFor reliability patterns, see `exa-reliability-patterns`.",{"name":5,"author":52,"license":15,"version":53,"description":54,"allowed-tools":55},"Jeremy Longshore \u003Cjeremy@intentsolutions.io>","1.0.0","Implement Exa load testing, auto-scaling, and capacity planning strategies.\nUse when running performance tests, configuring horizontal scaling,\nor planning capacity for Exa integrations.\nTrigger with phrases like \"exa load test\", \"exa scale\",\n\"exa performance test\", \"exa capacity\", \"exa k6\", \"exa benchmark\".\n","Read, Write, Edit, Bash(k6:*), Bash(kubectl:*)","main","90b50ed0778745a80fd5bfb13b1843d45b9e82f7","tests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Fexa-pack\u002Fskills\u002Fexa-load-scale",231,"https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust","https:\u002F\u002Fgithub.com\u002FDicklesworthstone","https:\u002F\u002Fwww.jeffreyemanuel.com\u002F","Building in NY","2026-11-12 03:15:57",{"source":8,"skillName":5,"commands":66,"prompt":76,"zipAvailable":77},[67,70,73],{"tool":68,"command":69},"npx","npx skills add Dicklesworthstone\u002Fpi_agent_rust --skill exa-load-scale",{"tool":71,"command":72},"bunx","bunx skills add Dicklesworthstone\u002Fpi_agent_rust --skill exa-load-scale",{"tool":74,"command":75},"pnpm","pnpm dlx skills add Dicklesworthstone\u002Fpi_agent_rust --skill exa-load-scale","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Fexa-pack\u002Fskills\u002Fexa-load-scale\u002FSKILL.md",true,[],[80,119,141,166,192,214],{"skillNo":81,"name":82,"nameZh":6,"description":83,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":84,"licenseFileUrl":85,"sourceHtmlUrl":86,"categories":87,"keywords":91,"publishedAt":47},"01M6FEGPPK0ZTKCCM0R3E3KS33","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","Apache-2.0","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FSKILL.md",[88],{"categoryNo":89,"categoryName":90,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118],"web artifacts builder","web","artifacts","artifacts builder","builder","frontend","css","components","react","component","routing","state management","state","shadcn","file","ui","Tools","Tailwind","use","html","single-file","simple","ui components","multi","for","jsx","suite",{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":84,"licenseFileUrl":123,"sourceHtmlUrl":124,"categories":125,"keywords":128,"publishedAt":47},"01M6FEE9VTK1W4GY21AKREJXRG","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FSKILL.md",[126,127],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":89,"categoryName":90,"taxonomyType":21,"taxonomyTypeDesc":22},[36,129,130,97,131,132,93,133,134,135,107,136,137,138,139,140,116],"webapp testing","webapp","screenshots","playwright","debugging","toolkit","browser","logs","applications","behavior","local","with",{"skillNo":142,"name":143,"nameZh":6,"description":144,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":145,"sourceHtmlUrl":146,"categories":147,"keywords":148,"publishedAt":47},"01M6FE20F7ZTQBFWKF4MPJ2SBX","neuropixels-analysis","Neuropixels neural recording analysis. Load SpikeGLX\u002FOpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen\u002FIBL curation, AI-assisted visual analysis, for Neuropixels 1.0\u002F2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fneuropixels-analysis\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fneuropixels-analysis\u002FSKILL.md",[],[149,150,151,152,153,154,155,156,110,157,158,159,160,161,162,163,140,164,165,24,116,29],"analysis","neuropixels analysis","spike","metrics","data","open","quality","user","recordings","Neural","motion","visual","quality metrics","unit","sorting","curation","recording",{"skillNo":167,"name":168,"nameZh":6,"description":169,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":84,"licenseFileUrl":170,"sourceHtmlUrl":171,"categories":172,"keywords":176,"publishedAt":47},"01M6FDP0PDK6F1GGX395C7625Z","skill-creator","Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fskill-creator\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fskill-creator\u002FSKILL.md",[173],{"categoryNo":174,"categoryName":175,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[177,178,179,180,181,182,183,184,40,185,186,187,188,189,140,116,190,29,191],"skill creator","creator","workflows","create","update","capabilities","knowledge","tool","specialized","guide","new skill","existing skill","users","Existing","new",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":196,"sourceHtmlUrl":197,"categories":198,"keywords":200,"publishedAt":47},"01M6FDM8Y7VK7NYG9SM7QPA3PW","notebooklm","Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fnotebooklm\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fnotebooklm\u002FSKILL.md",[199],{"categoryNo":174,"categoryName":175,"taxonomyType":21,"taxonomyTypeDesc":22},[194,201,202,203,204,205,206,135,207,208,110,209,210,211,212,116,213],"google","browser automation","gemini","automation","auth","code","library","management","only","document","query","Citation","source",{"skillNo":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":84,"licenseFileUrl":218,"sourceHtmlUrl":219,"categories":220,"keywords":227,"publishedAt":47},"01M6FDHPXE10J3XGTCH5HBHS1M","slack-gif-creator","Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like \"make me a GIF of X doing Y for Slack.\"","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fenterprise-communication\u002Fslack-gif-creator\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fenterprise-communication\u002Fslack-gif-creator\u002FSKILL.md",[221,224],{"categoryNo":222,"categoryName":223,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000005","邮件与沟通",{"categoryNo":225,"categoryName":226,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",[228,229,230,178,231,108,232,233,183,110,234,189,235,236,237,116,238,29],"slack gif creator","slack","gif","validation","constraints","Animation","me","make","Utilities","concepts","request"]